@inproceedings{williamson-etal-2021-intensionalizing,
title = "Intensionalizing {A}bstract {M}eaning {R}epresentations: Non-Veridicality and Scope",
author = "Williamson, Gregor and
Elliott, Patrick and
Ji, Yuxin",
editor = "Bonial, Claire and
Xue, Nianwen",
booktitle = "Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.law-1.17",
doi = "10.18653/v1/2021.law-1.17",
pages = "160--169",
abstract = "Abstract Meaning Representation (AMR) is a graphical meaning representation language designed to represent propositional information about argument structure. However, at present it is unable to satisfyingly represent non-veridical intensional contexts, often licensing inappropriate inferences. In this paper, we show how to resolve the problem of non-veridicality without appealing to layered graphs through a mapping from AMRs into Simply-Typed Lambda Calculus (STLC). At least for some cases, this requires the introduction of a new role :content which functions as an intensional operator. The translation proposed is inspired by the formal linguistics literature on the event semantics of attitude reports. Next, we address the interaction of quantifier scope and intensional operators in so-called de re/de dicto ambiguities. We adopt a scope node from the literature and provide an explicit multidimensional semantics utilizing Cooper storage which allows us to derive the de re and de dicto scope readings as well as intermediate scope readings which prove difficult for accounts without a scope node.",
}
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%0 Conference Proceedings
%T Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope
%A Williamson, Gregor
%A Elliott, Patrick
%A Ji, Yuxin
%Y Bonial, Claire
%Y Xue, Nianwen
%S Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F williamson-etal-2021-intensionalizing
%X Abstract Meaning Representation (AMR) is a graphical meaning representation language designed to represent propositional information about argument structure. However, at present it is unable to satisfyingly represent non-veridical intensional contexts, often licensing inappropriate inferences. In this paper, we show how to resolve the problem of non-veridicality without appealing to layered graphs through a mapping from AMRs into Simply-Typed Lambda Calculus (STLC). At least for some cases, this requires the introduction of a new role :content which functions as an intensional operator. The translation proposed is inspired by the formal linguistics literature on the event semantics of attitude reports. Next, we address the interaction of quantifier scope and intensional operators in so-called de re/de dicto ambiguities. We adopt a scope node from the literature and provide an explicit multidimensional semantics utilizing Cooper storage which allows us to derive the de re and de dicto scope readings as well as intermediate scope readings which prove difficult for accounts without a scope node.
%R 10.18653/v1/2021.law-1.17
%U https://aclanthology.org/2021.law-1.17
%U https://doi.org/10.18653/v1/2021.law-1.17
%P 160-169
Markdown (Informal)
[Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope](https://aclanthology.org/2021.law-1.17) (Williamson et al., LAW 2021)
ACL